Mathematical Modeling for Intelligent Systems: Theory, Methods, and Simulation

Mathematical  Modeling for Intelligent Systems: Theory, Methods, and Simulation aims  to provide a reference for the applications of mathematical modeling  using intelligent techniques in various unique industry problems in the  era of Industry 4.0. Providing a thorough introduction to the field of  soft-computing techniques, this book covers every major technique in  artificial intelligence in a clear and practical style. It also  highlights current research and applications, addresses issues  encountered in the development of applied systems, and describes a wide  range of intelligent systems techniques, including neural networks,  fuzzy logic, evolutionary strategy, and genetic algorithms. This book  demonstrates concepts through simulation examples and practical  experimental results.

Key Features:

• Offers a well-balanced mathematical analysis of modeling physical systems

• Summarizes basic principles in differential geometry and convex analysis as needed

•  Covers a wide range of industrial and social applications and bridges  the gap between core theory and costly experiments through simulations  and modeling

• Focuses on manifold ranging from  stability of fluid flows, nanofluids, drug delivery, and security of  image data to pandemic modeling, etc.

This book is  primarily aimed at advanced undergraduates and postgraduate students  studying computer science, mathematics, and statistics. Researchers and  professionals will also find this book useful.